A New Hybrid Intelligent Search Method to Find Global Optimal Solution for Engineering Problems
The complexity of engineering problems and the existence of various constraints on these issues, encourage the researchers to use of innovative methods based on a heuristic algorithm to find the optimal solution for practical problems at a cost-effective time and non-consistency tolerance. A distinction has been made between various issues and, therefore, extensive research has been done to improve heuristic algorithms in order to enhance their ability to solve engineering and practical problems. In this paper, due to the ability to global search some of the metaheuristic search patterns (such as the EMA algorithm) and the ability to local search for some meta-heuristic search patterns (such as the FPA algorithm), a novel combination method is proposed to use the ability of both types of algorithms. Then, using the proposed method, a hybrid search pattern with new abilities is presented, whose abilities are proven on standard benchmark testing functions as well as solving engineering problems.
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An Overview of the Concepts, Classifications, and Methods of Population Initialization in Metaheuristic Algorithms
Mohammad Hassanzadeh, Farshid Keynia *
Journal of Advances in Computer Engineering and Technology, Winter 2021